Software Engineer – Platform Security at FriendliAI (San Francisco, CA)

FriendliAI· San Francisco, CA·22h ago

Role details

Work type

Hybrid

Employment

Full-Time

Job description

About the job

FriendliAI is looking for an engineer to architect and build the security foundations of a multi-tenant serverless compute platform running on Kubernetes with hardened container isolation. As a Software Engineer, Platform Security, you will own the security design for both the control plane and data plane, implement guardrails as code, and partner closely with Platform/SRE/Infra teams to ship a secure-by-default developer experience. This is a hands-on builder and architect role.

Key Responsibilities

Design and implement the security architecture for a Kubernetes-based, multi-tenant serverless platform.
Build guardrails as code using Terraform and Helm.
Establish network segmentation and service-mesh policy.
Develop secrets and key management patterns.
Implement runtime detections for containerized workloads.
Design and roll out IAM & workload identity management.
Threat model new features and changes to the overall platform.
Collaborate with engineering to debug production issues, lead post-incident hardening, and automate evidence for compliance controls.

Qualifications

5+ years securing cloud-native platforms with a focus on distributed systems and multi-tenancy.
Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
Strong hands-on experience with AWS (IAM, VPC/networking, logging/monitoring, …) and Kubernetes/container security.
Proficiency with Terraform and Helm.
Experience building or operating runtime detections for containers/functions.
Strong technical background in backend systems, cloud infrastructure, or AI tooling
Clear written and verbal communication; ability to translate pricing/business rules into robust systems.

Preferred Experience

Knative or similar serverless-on-K8s frameworks.
Container hardening and sandboxing.
Policy-as-code and admission policy design at scale.
eBPF-based observability, detections, and signal tuning.
Multi-cloud exposure and cross-cloud identity approaches.
Hands-on contributions to SOC 2 / HIPAA control automation and audit evidence pipelines.

Benefits

A front-row seat to the generative AI infrastructure revolution
Competitive compensation and benefits package
Daily lunch and dinner provided; unlimited snacks and beverages
Health check-up and top-tier hardware support
Flexible working hours and a highly collaborative environment

About us

FriendliAI is building the next-generation AI inference platform that accelerates the deployment of large language and multimodal models with unmatched performance and efficiency. Our infrastructure powers high-throughput, low-latency workloads for global organizations and integrates directly with Hugging Face, providing instant access to over 600,000 open-source models. We are on a mission to deliver the world’s best platform for AI inference.

Why work at FriendliAI

Culture: “Boldest innovations come from great teams” – passionate, humble, curious builders. Mission-driven to democratize AI.
Work policy: Hybrid (San Francisco and Seoul offices); some roles are in-office (Seoul) or hybrid (SF). Employees engage in a mix of remote and on-site work.
Engineering focus: Heavy emphasis on AI inference engine, GPU kernels, Python developer tools, AI agents, backend, and platform security. High technical bar.
Perks: Not explicitly listed, but fast-growing startup with significant impact in the AI infrastructure space; opportunity to work on cutting-edge inference optimization.
Locations: San Francisco (HQ), Redwood City, CA, and Gangnam-gu, Seoul – global team with cross-cultural collaboration.

About FriendliAI

Company Overview

One-liner: FriendliAI is The Frontier AI Inference Cloud, providing a highly optimized platform for deploying, scaling, and monitoring large language and multimodal models with unmatched speed and cost efficiency.
Entity Type: Private (Seed stage; $26.7M total funding)
Headquarters: San Francisco, California, United States (with offices in Seoul, South Korea and Redwood City, CA)
Founded: 2021
Founders: Byung-Gon Chun (CEO) and Gyeong-In Yu (CTO) – the researchers who invented the continuous batching technique now standard in AI inference.

Core Business

Primary industry: AI Infrastructure / Cloud Inference Platform (Infrastructure as a Service)
Target customers: B2B – enterprises and AI teams deploying generative AI and agent workloads at production scale; focuses on open-weight and custom models.
Mission: Democratize access to production-grade AI so teams can focus on building great products.

Products & Services

FriendliAI Inference Cloud: A fully managed platform that instantly deploys 580,000+ Hugging Face models (language, audio, vision) with one click. Supports bring-your-own fine-tuned or proprietary models. Key features:
- Custom GPU kernels, smart caching, continuous batching, speculative decoding, and parallel inference.
- 2×+ faster inference than standard solutions, up to 3× faster than vLLM.
- 50% to 90% cost savings relative to closed model APIs.
- 99.99% uptime SLAs, geo-distributed infrastructure, enterprise-grade fault tolerance.
- SOC 2 Type II and HIPAA compliant (March 2026).

Market Standing

Valuation/Market Cap: Not disclosed (private company)
Key Metric: Total funding $26.7M (two seed rounds: $6.7M in 2021 and $20M led by Capstone Partners in September 2025)
Notable Investors/Partners: Capstone Partners (lead investor in latest round), plus two other investors in the first seed round.
Growth Signals:
- Headcount grew 90% YoY to ~45 employees (as of mid-2026).
- Active job postings: 19 positions (up 1800% YoY) – strong hiring momentum.
- Appointed Brian Yoo (former Moloco COO) as Chief Business Officer in April 2026 to drive hypergrowth.
- Achieved SOC 2 Type II and HIPAA compliance in March 2026, opening regulated markets.
- LinkedIn followers grew 257% yearly (8,221 followers).

Competitive Advantages

Inventor of continuous batching – the technique is now industry standard, giving FriendliAI deep technical expertise.
Purpose-built inference engine that constantly evolves for state-of-the-art models, delivering 2–3× speed improvements over alternatives like vLLM.
Massive model library – 580,000+ Hugging Face models deployable instantly with zero manual optimization.
Enterprise-grade reliability – 99.99% SLA, SOC 2 Type II, HIPAA, multi-cloud scaling.
Cost leadership – 50–90% savings vs. closed model APIs, maximizing tokens per dollar.

Strategic Focus

Hypergrowth – scaling sales, engineering, and solutions architecture teams globally (US and Korea).
Compliance and enterprise readiness – recent SOC 2/HIPAA certification to serve healthcare and regulated industries.
Multi-cloud and geo-distribution – expanding infrastructure footprint for global low-latency inference.
Open-weight and custom model support – enabling model ownership and flexibility for enterprises.

Sources